| Hi-index | 0.00 |
We tackle the problem of automating the categorization of companies according to their economic activities using business descriptions in free text format as input. This categorization is vital to fundamental aspects of national governmental administration such as short, medium and long term planning and taxation. As the number of categories considered is very large (more than 1000 in the Brazilian scenario), the automatic text categorization problem targeted here is challenging. We have applied and compared the use of two different techniques to deal with it: the Vector Space Model, a well known text categorization technique; and Virtual Generalizing Random Access Memory Weightless Neural Network, or VG-RAM WNN. To our knowledge, this is the first report on using VG-RAM WNN for text categorization.